Triple

T12038208
Position Surface form Disambiguated ID Type / Status
Subject Vinje E286593 entity
Predicate borderedBy P224 FINISHED
Object Tokke
Tokke is a rural municipality in Vestfold og Telemark county, Norway, known for its hydropower production, lakes, and mountainous landscapes.
 E960805 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tokke | Statement: [Vinje, borderedBy, Tokke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tokke
Context triple: [Vinje, borderedBy, Tokke]
  • A. Tokkō
    Tokkō was the colloquial name for Japan’s prewar and wartime Special Higher Police, a political police force tasked with suppressing dissent and ideological opposition.
  • B. Tocho
    Tocho is the common nickname for the Tokyo Metropolitan Government Building, a prominent skyscraper complex in Shinjuku that houses Tokyo’s metropolitan administration and offers popular observation decks.
  • C. Takanot
    Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
  • D. Takaro
    Takaro is a residential suburb located within the city of Palmerston North in New Zealand.
  • E. Tokoro
    Tokoro is a coastal district of Kitami City in Hokkaido, Japan, known historically for its fishing industry and drift ice along the Sea of Okhotsk.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tokke
Triple: [Vinje, borderedBy, Tokke]
Generated description
Tokke is a rural municipality in Vestfold og Telemark county, Norway, known for its hydropower production, lakes, and mountainous landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tokke
Target entity description: Tokke is a rural municipality in Vestfold og Telemark county, Norway, known for its hydropower production, lakes, and mountainous landscapes.
  • A. Tokkō
    Tokkō was the colloquial name for Japan’s prewar and wartime Special Higher Police, a political police force tasked with suppressing dissent and ideological opposition.
  • B. Tocho
    Tocho is the common nickname for the Tokyo Metropolitan Government Building, a prominent skyscraper complex in Shinjuku that houses Tokyo’s metropolitan administration and offers popular observation decks.
  • C. Takanot
    Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
  • D. Takaro
    Takaro is a residential suburb located within the city of Palmerston North in New Zealand.
  • E. Tokoro
    Tokoro is a coastal district of Kitami City in Hokkaido, Japan, known historically for its fishing industry and drift ice along the Sea of Okhotsk.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040a8be881908f4841145a7b4e86 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d8a9af881909e28783b0d83ed82 completed May 1, 2026, 12:33 p.m.
NEDg Description generation batch_69f53d930714819080f92d223d930389 completed May 1, 2026, 11:56 p.m.
NED2 Entity disambiguation (via description) batch_69f56505c0b481909f9caaf338f73033 completed May 2, 2026, 2:44 a.m.
Created at: April 8, 2026, 9:47 p.m.